Different GCMs yet similar outcome: predicting the habitat distribution of Shorea robusta C.F. Gaertn. in the Indian Himalayas using CMIP5 and CMIP6 climate models

Kaur, Sharanjeet ; Kaushal, Siddhartha ; Adhikari, Dibyendu ; Raj, Krishna ; Rao, K. S. ; Tandon, Rajesh ; Goel, Shailendra ; Barik, Saroj K. ; Baishya, Ratul (2023) Different GCMs yet similar outcome: predicting the habitat distribution of Shorea robusta C.F. Gaertn. in the Indian Himalayas using CMIP5 and CMIP6 climate models Environmental Monitoring and Assessment, 195 (6). ISSN 0167-6369

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Official URL: https://doi.org/10.1007/s10661-023-11317-3

Related URL: http://dx.doi.org/10.1007/s10661-023-11317-3

Abstract

Climate change impact on the habitat distribution of umbrella species presents a critical threat to the entire regional ecosystem. This is further perilous if the species is economically important. Sal (Shorea robusta C.F. Gaertn.), a climax forest forming Central Himalayan tree species, is one of the most valuable timber species and provides several ecological services. Sal forests are under threat due to over-exploitation, habitat destruction, and climate change. Sal’s poor natural regeneration and its unimodal density-diameter distribution in the region illustrate the peril to its habitat. We, modelled the current as well as future distribution of suitable sal habitats under different climate scenarios using 179 sal occurrence points and 8 bioclimatic environmental variables (non-collinear). The CMIP5-based RCP4.5 and CMIP6-based SSP245 climate models under 2041–2060 and 2061–2080 periods were used to predict the impact of climate change on sal’s future potential distribution area. The niche model results predict the mean annual temperature and precipitation seasonality as the most influential sal habitat governing variables in the region. The current high suitability region for sal was 4.36% of the total geographic area, which shows a drastic decline to 1.31% and 0.07% under SSP245 for 2041–60 and 2061–80, respectively. The RCP-based models predicted more severe impact than SSP; however, both RCP and SSP models showed complete loss of high suitability regions and overall shift of species northwards in the Uttarakhand state. We could identify the current and future suitable habitats for conserving sal population through assisted regeneration and management of other regional issues.

Item Type:Article
Source:Copyright of this article belongs to Springer-Verlag.
Keywords:Ecological niche modelling; Climate change; Uttarakhand; Shared socioeconomic pathways; MaxEnt; Central Himalayas.
ID Code:140825
Deposited On:10 Nov 2025 10:39
Last Modified:10 Nov 2025 10:39

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